Analogical Proportions, Multivalued Dependencies and Explanations

Show simple item record Link, Sebastian Prade, Henri Richard, Gilles
dc.coverage.spatial Paris, France 2022-11-09T20:32:02Z 2022-11-09T20:32:02Z 2022-10-10
dc.identifier.citation (2022). Scalable Uncertainty Management - 15th International Conference, SUM 2022, Proceedings, 13562, 351-360.
dc.description.abstract Analogical proportions are statements of the form “a is to b as c is to d”. They deal simultaneously with the similarities and differences between items, and they may be considered as a building block of analogical inference. This short paper establishes the existence of a close linkage between analogical proportions and (weak) multivalued dependencies in databases, thus providing an unexpected bridge between two distant areas of research: analogical reasoning and database design. (Weak) multivalued dependencies express a form of contextual logical independence. Besides, analogical proportions, which heavily rely on the comparison of items inside pairs and to the pairing of pairs exhibiting identical changes on attributes, are also a tool for providing adverse example-based explanations. Lastly, it is suggested that this may be applied to a data set reporting decisions in order to detect if some decision is unfair with respect to a sensitive variable (fairness being a matter of independence).
dc.relation.ispartof Scalable Uncertainty Management
dc.relation.ispartofseries Scalable Uncertainty Management - 15th International Conference, SUM 2022, Proceedings
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher.
dc.title Analogical Proportions, Multivalued Dependencies and Explanations
dc.type Conference Item
dc.identifier.doi 10.1007/978-3-031-18843-5_24
pubs.begin-page 351
pubs.volume 13562 2022-10-19T20:43:57Z
dc.rights.holder Copyright: The Author(s), under exclusive license to Springer Nature Switzerland AG en
pubs.end-page 360
pubs.finish-date 2022-10-19
pubs.start-date 2022-10-17
dc.rights.accessrights en
pubs.subtype Proceedings
pubs.elements-id 922559 Science School of Computer Science
pubs.record-created-at-source-date 2022-10-20

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